See observed visit patterns
Understand recency and frequency for identified shoppers.
Build a clearer view of who visits and who returns. Reach eligible past shoppers with relevant campaigns, and bring observed store response into your marketing decisions.
Grow an eligible shopper audience through participating guest WiFi.
Use visit patterns to inform the next invitation—not to infer what’s in the basket. Illustrative experience; businesses, profiles, and demo data are fictional.
A loyalty record and an observed visit answer different questions. Bring visit context into the way you plan audiences and measure campaigns.
Understand recency and frequency for identified shoppers.
Reach an eligible audience with a relevant local invitation.
Review attributed visits, or explore a suitable controlled study to measure lift.
Explore a few ways to turn customer context into a more relevant invitation.
Share a timely store update with eligible past visitors and give them a fresh reason to plan their next trip.
Choose a recency window that makes sense for your stores and use it to build an eligible audience.
Use the participating store as context for audience selection and reporting.
Fictional campaign examples. Audience eligibility, permissions, and supported channels depend on the setup.
Observed visits can show what happened after exposure. A properly designed holdout study can help test how much of the response was incremental.
Choose the audience, outcome, and measurement window.
Distinguish standard attribution from a controlled study.
Keep the result tied to the study’s scope and limitations.
Eligible shoppers included in the campaign.
A comparable group held out of the campaign.
Study design illustration only. Eligibility, controls, duration, and analysis require a separately agreed measurement plan.
Conceptual study diagram, not an actual experiment or a default reporting feature.
A three-week holdout study reported higher visit frequency among the exposed shopper groups.
Read the customer storyUse supported POS matching when transaction outcomes are part of the program. WiFi data alone does not reveal purchases, household characteristics, or product preferences.
Talk through your setupBring visit history into the customer picture.
Explore the productMake the next message more relevant.
Explore the productReach eligible past visitors again.
Explore the productConnect supported campaigns to observed visits.
Explore the productThe published study identifies its customer only as a national grocery chain. Its results should not be attributed to Gelson’s or another named brand.
No. It adds observed visit context. Loyalty membership and transaction details require their own supported data sources and matching.
Not automatically. Audience size, setup, study design, and available data affect whether a controlled test is appropriate. Review those requirements before planning a lift claim.
Explore a visit-based audience and measurement program for your stores.
See which ads drove real visits for one brand with 50+ locations, from month one to year six.